Book Image

CompTIA Data+: DAO-001 Certification Guide

By : Cameron Dodd
Book Image

CompTIA Data+: DAO-001 Certification Guide

By: Cameron Dodd

Overview of this book

The CompTIA Data+ certification exam not only helps validate a skill set required to enter one of the fastest-growing fields in the world, but also is starting to standardize the language and concepts within the field. However, there’s a lot of conflicting information and a lack of existing resources about the topics covered in this exam, and even professionals working in data analytics may need a study guide to help them pass on their first attempt. The CompTIA Data + (DAO-001) Certification Guide will give you a solid understanding of how to prepare, analyze, and report data for better insights. You’ll get an introduction to Data+ certification exam format to begin with, and then quickly dive into preparing data. You'll learn about collecting, cleaning, and processing data along with data wrangling and manipulation. As you progress, you’ll cover data analysis topics such as types of analysis, common techniques, hypothesis techniques, and statistical analysis, before tackling data reporting, common visualizations, and data governance. All the knowledge you've gained throughout the book will be tested with the mock tests that appear in the final chapters. By the end of this book, you’ll be ready to pass the Data+ exam with confidence and take the next step in your career.
Table of Contents (24 chapters)
1
Part 1: Preparing Data
7
Part 2: Analyzing Data
13
Part 3: Reporting Data
19
Part 4: Mock Exams

Updating stored data

Sometimes information changes, and you must update your dataset. In such cases, there are decisions that must be made. Each decision has pros and cons based on the reason you are collecting the data. For slowly changing dimensions, two cases often come up:

  • Updating a current value
  • Changing the number of variables being recorded

Updating a record with an up-to-date value

In most cases, you will simply add data points to the end of a table, but sometimes there is a specific value that is calculated or recorded that you need to keep as up to date as possible. Now, you have two options:

  • Overwrite historical values: If you just change the value in the cell, this keeps your dataset much smaller and simpler. However, because you have lost what your value was, you no longer have access to historical data. Historical data has many uses and is required for trend analysis. If you don’t care about predicting future values of this number...